Satellite map of the ocean off the west coast of Africa (Source: Jose A. Piedra-Fernandez, University of Almeria, Spain)

Researchers plan to improve the program and use it to track changing environmental conditions

Penn State and University of Almeria researchers have built a computer program that is capable of monitoring and analyzing large amounts of satellite data in order to assist scientists in tracking changing environmental conditions.

James Wang, professor of information sciences and technology at Penn State, and Jose A. Piedra-Fernandez, an assistant professor of information sciences and technology at the University of Almeria in Spain who is currently visiting Penn State, have designed the program to study a vast amount of satellite data and images in an attempt to monitor the ever-changing and intricate environmental conditions. They are mainly focused on analyzing mesoscale regional ocean features within the images produced by satellites.

"All of the data and information that is continually collected by satellites and sensors can cause tons of problems for scientists, who simply don't have the time to analyze every pixel of every satellite image," said Wang. "Our goal has been to provide a tool that would create useful information or knowledge from this large pool of data."

To make this program, Wang and Piedra-Fernandez created a database of ocean structures and taught the program to recognize changes in the ocean. The computer program is similar to a Bayesian network, which uses probability to make decisions. Wang and Piedra-Fernandez made sure to make the program as complex as the climate itself by separating ocean regions from land regions, adjusting for possible earth-and-solar-based interference sources, and identifying features from particular regions of ocean. The program is then able to filter regions of the images by ranking relationships between features on scale based on relevance and strength. This allows the computer to recognize oceanic features like wakes, upwellings and eddies.

Researchers then tested the computer program on satellite images of oceans in the Mediterranean Coast, the Iberian Atlantic and close to the Canary Islands. The images were provided by the National Oceanic and Atmospheric Administration and the Advanced Very High Resolution Radiometer. The tests consisted of over 1,000 real oceanic features, made up of 472 upwellings, 119 cloudy upwellings, 180 wakes, 40 cyclonic eddies, 10 anticyclonic eddies and 180 "misclassified" regions.

"In almost all cases, the proposed methodology improves the accuracy rate and reduces the number of features necessary to get a good ocean structures classification," said Piedra-Fernandez.

The next step is to add features such as chlorophyll and salinity concentrations. Researchers would also like to improve the image classification system.